Streamline Certificate of Analysis Processing with Generative AI
As the consumer packaged goods industry continues evolving, efficient quality control remains crucial for maintaining product safety and regulatory compliance. Processing certificate of analysis (COA) documents is a critical quality control step, but its time-consuming nature slows production. These quality control documents often arrive with shipments from suppliers in multiple, loosely defined formats that evolve over time — sometimes unexpectedly — making automation difficult. Amazon Bedrock Data Automation (BDA) offers a streamlined approach using generative AI to automate COA processing.
Technical Challenges of COA Automation
For technical teams in CPG and manufacturing, COA processing is a significant challenge. Before accepting deliveries, manufacturers must verify that each supplier batch meets stringent safety standards and regulatory requirements. Lack of formal standards, wide layout variability and frequent changes in document formats make traditional automation approaches ineffective and expensive. These factors require technical teams to spend time and money training custom AI models to fit each document format individually. When formats change, models must be retrained before processing the new format. Because of this complexity, COA workflows tend to remain manual, reducing production efficiency and complicating compliance and audit tracking.
Simplicity of Generative AI–Powered Services
BDA, a generative AI–powered, intelligent document-processing solution, transforms how companies handle these essential documents. It automatically classifies, extracts and validates data from diverse COA formats while maintaining the accuracy and traceability required for compliance. And it doesn’t require complex and expensive model training ahead of time. This intelligent automation helps quality assurance teams focus on critical decision-making rather than manual data entry.
Getting Started
Begin by first creating a blueprint for your COA in the AWS Console for BDA, which lets you define the fields you want to extract and how to identify them. In addition to extracting fields from text, BDA also gives you the ability to work with documents that have tables and images. Once you have a blueprint, upload a sample document for a preview of the data BDA identifies, then adjust your definitions. As output, BDA provides the data you requested, along with confidence scores. You can use this information to decide if you want to defer to a human for closer review.
Beyond extracting explicit data from your document, you can also define implicit fields, which aren’t directly stated in the data but can be derived or transformed from existing information. It can identify and evaluate multiple data points in the COA document, using them in calculations or evaluations, such as setting a compliance field to “true” only if all specified rules are met. Since rules can be written using simple English instructions, you don’t need to write formulas or code. This flexibility allows BDA to handle diverse document layouts and easily extract meaningful insights from unstructured text.
End-to-End Automation and Integration
Once you’ve created blueprints, you can organize them into a BDA project. Each project can contain up to 40 blueprints, allowing you to handle multiple document types efficiently. When you submit a document for processing, BDA automatically selects the most appropriate blueprint based on its content. This enables automated processing across different ingredients, suppliers, and COA formats.
After a project is ready, you can integrate BDA into a workflow. For example, a delivery arrives at your facility. The driver hands a COA document to your facility manager. The facility manager uses a simple application to scan the document and save it to your company’s cloud environment. Saving the document triggers the workflow. The facility manager moves on to other tasks while the workflow orchestrates the necessary processing actions. Based on the BDA output and compliance calculation, the workflow can send the document’s compliance status to your facility manager, so they’ll know when the shipment is clear to unload.
Next Steps
Organizations can begin their COA automation journey by identifying high-volume ingredient categories that would benefit most from automated processing. Start with standardized COA formats from major suppliers, then expand to handle more complex document variations as the system matures.
By embracing generative AI, CPG manufacturers can transform their COA processing workflows, leading to more efficient operations, more flexible processes, reduced costs, and improved product quality assurance. In an increasingly complex marketplace, innovative technologies like BDA will play a crucial role in maintaining competitiveness and ensuring product safety.
To learn more about BDA, read the getting started guide, view the Guidance for Accelerated Intelligent Document Processing on AWS solution for a full-scale sample of an end-to-end document processing implementation, or contact AWS.
